SPRING Reasoning and judgement

Question 1

describe the sally clarke problem

Answer 1

both babies die from sudden infant death - very unlikely
argued that prob so low, more likely to be murder
but lawyers used poor statistical reasoning - two events were not independent of eachother and the prob of two independent events not the same as two linked ones (prosecutors fallacy)
ignores probabilities of two murders in same family

Question 2

contraceptive probabiities

Answer 2

98% vs 99% effective

over time, 98% sig less effective than 99%

Question 3

how do we make subjective probability judgements

Answer 3

decision making based on SEU

heuristic strategies to judge the likelihood of event occurance

Question 4

describe the availability heuristic

Answer 4

judge probability based on ease comes to mind

if more freq then more available

Question 5

tversky and kahenman availability heuristic

Answer 5

more common: r as first or third letter

most say first - easier to think of words beginning with r

Question 6

slovic, fichoff and litchenstien 1979 availability heurostic

Answer 6

estimate freq of causes of death

overestimate those unlikely but heavily reported ie murder and underestimate those rarely reported ie emphysema

Question 7

describe the representativeness heuristic

Answer 7

degree of correspondence between an instance and a category
ie looks and sounds like it so probably is
how much a certain set of circumstances will drive the likelihood of something based on past experience - link closely to stereotypes

Question 8

tversky and kahenmen 1983 conjunction fallacy (representativeness heuristic)

Answer 8

liinda - bank teller, feminist bank teller, feminist
often chose feminist bank teller but statistically the least likely
two independent events make conjunction of two together even less probable - feminist bankteller is smaller subset of banktellers

Question 9

describe anchoring heuristic

Answer 9

base estimated probability on the first piece of information we are given

Question 10

tversky and kahenman 1974 anchoring

Answer 10

estimates under time pressure 
1. 1x2x3x4x5x6x7...
2. 7x6x5x4x3x2x1
= ~40000 
BUT estimate 1 lower than 2 based on first numbers

Question 11

lichtenstein et al 1978 anchoring

Answer 11

achoring on first given value means fail to adjust appropriately
estimate freq of 40 causes of death
a. 50000 motor cycle or b.10000 electrocution
estimate higher for a

Question 12

real world examples of anchoring

Answer 12

anchoring consumers for price reference so view as less expensive
credit card minimums
high prices as ref point for lower

Question 13

what is bayesian reasoning

Answer 13

update probabilities based on additional information that causes to ignore the original base rate and focus on hit rate
make probabalistic inferences based on additional info and therefore forget the initial info given

Question 14

kahenman and tversky 1973 base rate fallacy

Answer 14

30 engineers and 70 lawyers
stereotypical description of engineer/lawyer or neutral
neurtral tend to report 50%
rate increase if stereotypical
BASE RATE ALWAYS THE SAME: 42%

Question 15

medical diagnosis problem base rate fallacy

casscells et al 1978

Answer 15

prob breast cancer 1%…given values of pos mamog if have cancer = 80% and not = 9.6%
= overall 7.8% prob
clinicians probability = 70-80% as ignore probability of 1% and focus on hit rate

Question 16

gigerenzer, hofferage and ebert 1998 bayesian reasoning

Answer 16

positive HIV test - prob that ACUTALLY positive?

clinicians say 100% even if low risk patient

Question 17

gigerenzer and hofferage 1995 format of decision

Answer 17

if way info is presented is more reflective of the way we make decisions in real life then more likely to interpret in correct way
ie breast cancer problem in frequency format and most people get correct

Question 18

cosmides and tooby 1996frequentists hypothesis

why are frequency problems easier

Answer 18

inductive readoning = prob in the form of freq

easier to break down if in freuqncy form - tree

Question 19

girotto and gonzalez 2001 defective frequencies

Answer 19

if not given enough info to complete freq tree OR the information given is all drawn from multiple samples

Question 20

how might you improve bayesian reasoning problems

Answer 20

change structure of the info not the format

apply cumulative reasoning

Question 21

what are naive probabilites

Answer 21

when people make judgements on probabilities they are not expert in - relate to the alternatives they consider
ie not given probabilties then assume equiprobable

Question 22

girotto and gonzalez 2001 prob and freq use

Answer 22

prob not alwats bad ie can format as chance to improve interpretation
freq not alwats good - come harder than probabilities, dependent on the info structure

Question 23

mccloy byrne and johnson laurd 2010 improveing bayesian readoning

Answer 23

naive individuals dont use binomal formula to calc cumulative prob and instead use conjunctions ie if not yet occred then the prob = 0/no. trials
those who recog that freq cumulates over time may still underestimate the rate of increased risk
improve by presenting problems in specific ways - ie more structured layout

Question 24

johnson laird et al

sentanial resoning

Answer 24

when an individual understands discours and imagines a state of affairs then constructs mental models of the relevant situation
prepresents the possibilities and diff ways they might occur - represents explicitly what is true but not what is false
each model therefore represents an equiprobable alt unless info given to hold belief of the contrary
the greater the no of mental models a task elicits and the greater their complexity the worse the performance

Question 25

equiprobable sentenial reasoning example

Answer 25

box with red or black marble or both
prob of black marble with another marble?
- tend to say 2/3 as no info given about prob - ill specified

Question 26

define prosecutors fallacy

Answer 26

tendency to ignore that to occurances are not statistically independent from one another and therefore the probability of the two occuring is lower (more likely) than if they were independent

Question 27

how did sally clarkes case fail to prosecutors fallacy

Answer 27

argued deaths of two newborns statistically independent = 1/72m and that this equates to the prob that guilty
BUT NOT - sig lower prob because share same environment

Question 28

define bayesian reasoning

Answer 28

a means of quantifying uncertainty
rule for refining an hypothesis by factoring in additional evidence and background information, and leads to a number representing the degree of probability that the hypothesis is true
- ie accounting for independence of events in prosecutors fallacy

Question 29

define subjective probability

Answer 29

the extent to which a coherent person believes that a statement is true based on the info that is available at that time
use of heuristics to form a subjective judgement

Question 30

seidelmeier hertwig and gigerenzer 1998

availability heiristic

Answer 30

memory often good at stoing freq info
tend to measure ease info comes to mind based on no instances retrieved in given time frame and speed of retrieval
BUT - some predictions where overestimate low freq and underestimate high so not always completely accurate

Question 31

describe linda

t+k conjunction fallacy

Answer 31

31 y/o outspoken and bright
major in philosophy
concerned with discrimination and social justice
participates in antinuclear demonstrations

Question 32

diff subective prob judgements

Answer 32

availability heuristic
representativeness heuristic
anchoring

Question 33

bayesian reasoning prob

Answer 33

base rate fallacy
medical diagnosis prob
hiv screening
prob vs freq vs chance